<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Voice-Ai on René Zander | AI Automation Consultant</title><link>https://renezander.com/tags/voice-ai/</link><description>Recent content in Voice-Ai on René Zander | AI Automation Consultant</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 23 Apr 2026 09:00:00 +0000</lastBuildDate><atom:link href="https://renezander.com/tags/voice-ai/index.xml" rel="self" type="application/rss+xml"/><item><title>Voice AI in Production: From RunPod to Hosted Kubernetes</title><link>https://renezander.com/blog/voice-ai-production-kubernetes/</link><pubDate>Thu, 23 Apr 2026 09:00:00 +0000</pubDate><guid>https://renezander.com/blog/voice-ai-production-kubernetes/</guid><description>&lt;p>Your voice model works in a demo. The same model in production stalls under concurrent load. The model file is identical. So is the GPU card. Only the deployment changed.&lt;/p>
&lt;p>If your TTS service runs on a single RunPod pod, you&amp;rsquo;ve already met this wall. You handle one request per GPU at a time. A crash costs ninety seconds to reload the model. Failover isn&amp;rsquo;t in the setup. Your marketing page says &amp;ldquo;generate narration instantly.&amp;rdquo; Your infrastructure says &amp;ldquo;please form an orderly queue.&amp;rdquo;&lt;/p></description></item></channel></rss>